Data-Processing-for-3D-meshes

Tensors and Dynamic neural networks in Python with strong GPU acceleration

30 days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than100 days, follow your own pace. These videos may help too: https://www.youtube.com/channel/UC7PNRuno1rzYPb1xLa4yktw

Python Data Science Handbook: full text in Jupyter Notebooks

The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more

Visualizer for neural network, deep learning and machine learning models

The fundamental package for scientific computing with Python.

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

matplotlib: plotting with Python

? The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools

A high-performance, zero-overhead, extensible Python compiler with built-in NumPy support